Predictive torque control of induction motor for rotor bar faults diagnosis
Unlike DC motors and synchronous motors, they are maintenance-free motors due to the absence of brushes, commutators and slip rings. Induction motors can be operated in polluted and explosive environments as they do not have brushes which can cause sparks. In this paper, the performance of two control techniques, namely direct torque control (DTC) and predictive torque control (PTC), are compared in transient and static states when applied to a faulty induction machine (IM). The current and torque ripples is evaluated in a healthy machine, as well as in the presence of faults, at various speed and load values. During the transient state, the objective is to assess the method that provides the optimal dynamic response, which is achieving the desired speed without any overshooting while during the static state, the objective is to minimize torque ripple and harmonics in the stator current. The Discrete Wavelet Transform (DWT) is used to analyze stator phase current. In addition, the energy eigen value (EEV) analysis has been used to determine the fault severity. The healthy and faulty systems are simulated using Matlab/Simulink for the two control methods. The results show the superiority of the PTC method compared to the DTC. A comparison of the proposed control method with other works reported in the literature is performed to verify the superiority of the proposed strategy.
History
Citation
Tarek Bedida, Salim Makhloufi, Youcef Bekakra, Mostefa Kermadi, Noureddine Bessous, Ridha Kechida, Djamel Taibi, Predictive torque control of induction motor for rotor bar faults diagnosis, Energy Reports, Volume 11, 2024, Pages 4940-4956Author affiliation
College of Science & Engineering EngineeringVersion
- VoR (Version of Record)
Published in
Energy ReportsVolume
11Pagination
4940 - 4956Publisher
Elsevier BVissn
2352-4847eissn
2352-4847Acceptance date
2024-04-26Copyright date
2024Available date
2024-06-20Publisher DOI
Language
enPublisher version
Deposited by
Dr Mostefa KermadiDeposit date
2024-06-13Data Access Statement
No data was used for the research described in the article.Rights Retention Statement
- No